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- W2967820348 abstract "Image enhancement is a preprocessing step required in most image processing and computer vision applications because a high quality image leads to better and accurate processing results. Usually the image quality is subjectively associated to its contrast, but, by increasing the contrast, other distortions can be created. In this paper is proposed a context-free image enhancement method based on the multi-objective Particle Swarm Optimization algorithm combined with chaotic sequences. As objective functions, the expected contrast gain and tone distortion are used. The experiments revealed that for the particle swarm algorithm the results are better when the chaotic maps are used instead of the standard random evolution. The results are also superior to those obtained by the traditional histogram equalization method." @default.
- W2967820348 created "2019-08-22" @default.
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- W2967820348 date "2019-07-01" @default.
- W2967820348 modified "2023-09-26" @default.
- W2967820348 title "Image Enhancement using Chaotic Maps and Bio-inspired Multi-objective Optimization" @default.
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- W2967820348 doi "https://doi.org/10.1109/isscs.2019.8801793" @default.
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